Immersive Virtual Reality for Pain-related Movement Dysfunctions in Patients With Chronic Shoulder Pain

Overview

The goal of this clinical trial is to the use of VRi specified effects on pain, kinesiophobia, fear of pain, disability, self-efficacy, grip strength and range of motion in motion in people with chronic shoulder pain. The main question\[s\] it aims to answer are: * Can specific immersive virtual reality software decrease movement-evoked pain in patients with chronic shoulder pain compared to non-specific software? * Can specific immersive virtual reality software increase shoulder flexion range of motion in patients with chronic shoulder pain compared to non-specific software? Participants will use a specific VRi software compared with non-specific VRi software

Studio Design Randomized controlled clinical trial (RCT). This protocol follows the indications of the guidelines for Clinical Trial Publications (CONSORT) and will follow the TIDIER check-list for the exhaustive description of the interventions that will be performed. Target population Patients with persistent musculoskeletal shoulder pain aged 18-65 years primary chronic musculoskeletal pain, according to the International Classification of Diseases-11 (2019) of the International Association for the Study of Shoulder-related Pain (IASP). Sample size calculation A total of 30 individuals for each treatment group will allow to detect, in numerical variables, differences between pairs of group means of a magnitude (Visual Analogue Pain Scale) corresponding to 1.5 points of the standard deviation, with an effect size of 80% maintaining the type I error at a level of 5%. Taking into account a loss of 10%, it would be necessary to include 33 individuals in each group. Interventions This is a randomized clinical trial (RCT) of 2 parallel groups (ratio 1:1) that will be carried out in the Teaching Care Unit (UDA) of the Faculty of Health Sciences of the University of Malaga (UMA). The study protocol conforms to the items of the Recommendations for Interventional Trials (SPIRIT) and the RCT will conform to the Consolidated Standards for Reporting Testing (CONSORT). Recruitment: Patients will be recruited by invitation to participate via email to the university community, as well as contact with Family Medicine professionals for the referral of patients who meet the inclusion criteria will be invited to participate in the RCT. Doctors involved in the recruitment process will receive a clinical session to ensure that the selection process is carried out according to the inclusion criteria and that participants do not meet the exclusion criteria. Patients will receive oral information and a written document (Patient Information Sheet). If the patient is interested in participating in the study, after signing the informed consent, he will be summoned to be evaluated by an external evaluator who will perform the initial assessment. The patient will also receive a revocation sheet in case they decide to leave the study at any time. After the initial assessment, participants will be randomly assigned to one of two study groups (experimental or control). Randomization After the initial evaluation, each patient will be assigned an alphanumeric code for the identification of each subject, thus respecting their anonymity. To perform the randomization procedure, the principal investigator (PI) will receive a list of the alphanumeric codes of the participants and perform a random assignment using the SPSS statistical package. Blinding An independent biostatistician will perform the statistical analysis without knowing the treatment performed by each group. Participants and physiotherapists performing the intervention cannot be blinded, but the physiotherapists performing the intervention are not involved in the patient assessment process. Similarly, the evaluator will also be unaware of the participant assignment group in order to establish blinding of the evaluator. Intervention * Control group: The control group will perform a VRi placebo intervention with the game "Tsuro", which consists of a puzzle-based strategy game where the patient will have to solve a maze by placing pieces. This intervention will attempt to assess the influence of the immersive context and the playful component compared to the intervention group. This treatment will last 3 sessions / week of 15 minutes, therefore taking a total duration of two weeks of treatment with a total of 6 sessions. * Intervention group: You will perform active treatment using Virtual Reality software based on pain education and gamified exercise for gradual exposure to shoulder movement. The game involves visual stimuli and shoulder movement exercises in the shoulder flexion and abduction ranges in real time using immersive glasses located on the head and two controls on both hands. Patients will inhabit an avatar from an egocentric perspective. The intervention will last 3 sessions / week of 15 minutes, therefore carrying a total duration of two weeks of treatment. Within the intervention will consist of a pill of education in pain neuroscience (PNE) of 1 minute duration, followed by an exposure level that will last 2:30 minutes where a progression will be made in number of ranges of motion and speed. Each session will consist of 2 intervention blocks (PNE + Gradual Exposure). The content of the PNE educational pills have been selected according to the objective of the study. * Pain as an alarm system * Protectometer * Persistent pain, characteristics * Persistent pain Why? * Persistent pain, neuroplasticity * Sensory and interpretation component * The complexity of the body * Threshold depends on context * PD, Sensitivity * Imaging tests * Negative effects of imaging tests * The solution is in you Data collection procedure The study protocol will be recorded in Clinicaltrials.gov, prior to data collection. Who will collect the data: A physiotherapist with experience in managing people with persistent musculoskeletal shoulder pain and training by the research team will be responsible for data collection. When data will be collected: Pain variables during movement and range of motion and grip strength will be measured before the intervention and after the intervention in each treatment session Demographic variables will be collected at the beginning of the study. Finally, the variables of Self-efficacy, Kinesiophobia, Fear of pain and disability will be collected at the beginning of the intervention and at the end of the intervention after 1 week of treatment. How the data will be collected: all variables will be measured with the self-reported questionnaires discussed in the table above, since they are validated and reliable measures to assess these factors. Data analysis All data will be evaluated to check the normality of its distribution. The numerical variables will be summarized with means and standard deviations and the categorical ones with percentages. Numerical variables that show a distribution far removed from normal will be transformed to obtain distributions close to normal, or otherwise, they will be summarized by using percentiles. For the graphical representation of the distribution of the numerical variables in each treatment group, we will use box and whisker graphs. To represent categorical variables, pie charts will be used. In order to test the equality of means for numerical variables, we will apply Student's T if the distributions are not far from normal. Otherwise, we will calculate the Wilcoxon-Mann-Whitney statistics. Depending on the observed response to treatment in numerical variables or the observed change in them, we will construct several definitions of success/failure for the treatment outcome in individuals. We will adjust logistic regression models to predict treatment success. These models will include those variables that show a statistically significant relationship with the corresponding outcome variables in the univariate analysis. It shall be considered as statistically significant p-values below 0,05. All models will be adjusted for age, gender, pain intensity and pain duration. These variables will be used as adjustment variables due to their importance as factors associated with chronic pain The analysis of the data will be carried out through the use of statistical software